We recently sat down for a conversation with Martin Casado of Andreesen Horowitz. The transcript below has been lightly edited for clarity.
Bruce Davie (BD) - Okay, so I'm here today with Martin Casado. We're doing another episode
of Coffee with Bruce. Martin, welcome.
Martin Casado (MC) - Happy to be here with
my chrysanthemum tea.
BD - Alright, yeah. Dealing with time zones and all, it's kind of late for coffee there, I guess. So, Martin Casado really needs very little introduction but in case you've been living under a rock, Martin was one of the founders of Nicira, was the person who successfully recruited me to go and work at Nicira, starting off an eight year journey into network virtualisation for me. And these days he's a general partner at Andreessen Horowitz. And so Martin, I've got a few things I wanted to talk about today. First of all, I want to talk a little bit about some of the things we experienced at Nicira in the early days of network virtualisation.
I think when I joined, you guys had already established that you had this plan to disrupt networking and change it in a pretty significant way. So I guess first thing I wanted to say looking back now, I think it was what 2007 that you founded Nicira. It's a lot of years to look back on now. Are you happy with where things ended up?
Martin Casado (MC) - So yes. Yes, I'm quite happy.
It's interesting though, when we started the company, if you would have looked at what our aspirations were, it was "start with the data center and then change all of networking". And every new bit of networking is another feature on the same technical platform.
And it turns out, every new bit of networking is actually a separate industry, right?
So I think originally we had pretty broad ambitions, which it's fun to see the industry play out totally independent of what we're doing. I mean, that's been fantastic.
But if you look at, I was actually looking back. If you look at our Series A deck, when we're like, okay, we're going to start, and we're going to focus on the data center and network virtualisation. If you look at the timelines that we played out and what actually happened, it was actually pretty much in line.
And so I think in the area that we decided to focus on, you know, it's been great to see the realisation.
BD - Yeah, and honestly, SD-WAN for me is just the continuation of the Nicira vision. It's just that it got done by other companies. And the first time somebody explained SD-WAN to me, it was like, oh, you're doing what Nicira did, but you're gonna do it for the WAN.
And so to that extent, the vision has actually played out quite, quite broadly. It's just, as you say it, wasn't on a single technical platform.
MC - I know that's exactly, yeah. I think that's exactly right. The lower you go in the stack, the more general the technology, isn't it? So at some level a compiler company is basically every software company on the planet, right? Because you can build anything with a compiler.
So I think that the industry - and we were a very important part of the discourse - the industry at the time was kind of grappling with what does software-defined networking and network virtualisation mean? I think that what we distilled in that discourse was the right way to build networks, all aspects of networks.
But when it comes to the brass tacks of building a company, who you sell to dictates the kind of company you are, and the specific problems you're tackling dictate the type of engineering organisation that you build.
And what I didn't appreciate that I appreciate now is, absolutely SD-WAN is very much part of the original vision that we had, but how much effort it takes to execute in these separate verticals.
Which is why it's actually so exciting to see companies pull this off. That have both data center and WAN solutions, because they actually have so much potential synergy, but for a startup that's a hard thing to execute on.
BD - Yeah, also you sort of getting onto another thing I want to talk about here, which is actually what kind of company you wanted to build, I thought the culture at Nicira was pretty amazing. My biggest regret is I didn't join earlier just because it was so much fun.
But what was in your mind about how to build the culture? What did you do to go and create the culture at Nicira? And I mean, what are your thoughts on that more broadly.
MC - In some ways, one of our greatest challenges was also our greatest gift. And that was, we started the company in 2007 and then the world ended about a year later, right? If you'll remember with the great recession. And it was like the nuclear winter had set in.
And you probably had two options, which is you band together or you die. And I think that in many ways our culture was galvanised in this tough time. And what it forced in particular is for the company to have a very clear vision that you can march towards. And if the vision wasn't clear, people wouldn't have done it. I mean, they just wouldn't have, just because it was such a scary time.
And so I think 2008, 2009, we just really, really sharpened a vision that everybody believed in. And if someone didn't believe in it they'd speak up because they didn't have anything to lose.
And then we had iterated by the time things were starting to improve, that vision was very clear. And then I think what happened is once you have a vision that you believe in, the work is really realising that vision and an implementation of building product, which it's something that we've just been desperate to do anyways. And so I do think a lot of this was galvanised by, having a tough time.
And I think that being mission focused is something people talk about a lot and it's like, these are the three things on my badge or whatever. And I think that kind of misses the point, which is if you don't have a very high definition kind of like the mountain top that you're tackling, I think people start just meandering in the woods. And I think that was very, very core to the cultural success of the company.
BD - Yeah and to be honest, I've talked about that in terms of how you led the NSBU when we were at VMware together was, I think every staff meeting you would tell us, you know, these are the three things that we're shooting for this year. And you would repeat it every week so that nobody could have any doubt what direction the organisation was moving.
MC - It's always been amazing to me how easy is to lose focus of even very simple things. We're a room of very professional adults at that peak of our career. And we're talking about very simple things like KPIs.
But I do think in many ways being an operator is managing your own psychology and the hardest part of managing your own psychology is just staying focused on the things that are really important and taking a long view.
And so one thing that I loved as a group that we did is, everybody had the same expectation that we're going to make sure that we're staying on track for a broader goal, and everything is subservient to that.
And I mean, listen I sit on 17 boards now, and I can't tell you how rare that actually is, that people will actually distill all of the trouble and all of the pain, and all of the excitement until you get fairly simple to articulate goals.
BD - What about now that we're moving to this world of much more distributed teams, given the COVID impact on remote working, does that affect the way you think about building a team culture in a startup?
MC - This is one of the big questions that we're trying to answer right now. I think maintaining culture and building culture are actually two different things. In my experience, maintaining culture is something that you can kind of doing the same motions but you may have to do more of them and you may have to adapt them online, but it's not that interesting of a conversation. Does that make sense?
Which is like, yes, you should do it online. Yes, you should have more touch points. Yes, should you be sensitive to people in their personal issues. But these are fairly straightforward conversations to have and you can maintain a strong culture. And quite frankly, we've seen cultures getting even stronger because there's a notion of solidarity, through that.
What I don't know the answer to and I wish I did have an answer because I think everybody's trying to figure it out is, can you create a new culture, right? Can you change a culture?
And I think about - a lot of times - Andreessen Horowitz is a venture firm for example. I mean, it's pretty remarkable to create a tier one venture firm in 10 years, right? It just doesn't happen very often.
And then I ask the question could you do that in the time of COVID, right? Like for sure you can stay being a firm. And so I think it's a great question. I wish I had a better answer, but I would encourage anybody thinking to this to really decouple the two issues of maintaining culture and creating culture.
BD - Yeah, it's going to be fascinating to see how this plays out in the next few years.
So, one of the areas that I've been really interested in for the last few years, and I know you've written about it quite a bit is, is AI and machine learning. And also, I love the fact that when you talk about it, you often talk about it in terms of economics. Because I go all the way back to listening to David Clark at MIT talk about the idea that we should all be economists because you can't really understand networking, unless you think about the economic impact of your design decisions.
What's your thinking about the economics of AI businesses?
MC - Let me actually start with the economics of cloud businesses because it's very interesting. And then we'll back into the economics of AI.
So let's talk about the life cycle of a company that's built in the cloud. So, you know, Bruce Davie creates Bruce Davie inc, and comes to Martin Casado and says, "Hey, Martin, you know, give me $2 million to do my company."
BD - The scenario could totally happen by the way.
MC - So, we're like here, Bruce here's 2 million bucks and you're off looking for product market fit. Now you come back and like, there's some interest here, give me $10 million. So I'll give you $10 million and I join your board.
And so now what happens for every board meeting, the questions I ask are: what's growth look like? What features are we shipping?
And so you're telling your R&D organisation, we need to grow, we need new features. And that's basically your entire focus. Never once do we talk about things like gross margin or COGS right? And COGS are cost of goods sold, like how much it costs to run this stuff. So you're writing horribly suboptimal code on AWS or wherever.
So, you're doing this and then you've got a real business to say you're 50 million in ARR. You're feeling good and now you've got a real financial investor. Like I'm an investor that invests in ideas and people. And like, right, Bruce is the smartest architect I've ever worked with. Like, this is a great space. Like whatever, I'll invest just in that.
But financial investors actually care about financial metrics, like unit economics, and things like margins matter because they directly impact profitability. So then they look at your company and they're like, hey, listen, this is all great. You've got great growth but basically for every dollar you're making 50 cents goes to Amazon.
You got this huge issue now, which is you spent four years building an R&D team and a business practice around growth because that's what all of the economic incentives including the board have told you to do. And you've got a company now that has low multiples because you've got low margin, right? And then you've got this paradox, what do you do?
So more and more, what we're seeing as soon as companies slow down, they do, what's called repatriation. They're like, listen, like you can't fix that much code. I mean, it took Dropbox years to do it. So we're going to have to find some way to move it onto our own infrastructure or something else to improve those margins.
And I would say there's probably, in SaaS companies as they slowed down, billions of dollars trapped in this margin issue for these companies that are going to the cloud.
Okay, so this is the life cycle you're focusing on growth. You write poor code, you have these kind of relatively fat margins, and now you have to do something about it because it's impacting your valuation. Instead of being valued at $10 billion or $20 billion, you're valued at $10 billion. We're talking about a lot of money that's being impacted.
Okay, so the question with AI/ML to bring it back to that, is it's not clear in the case of the cloud, you could be like, well, I'm paying somebody else, if I do it myself, I can do it cheaper. And maybe if I re-architect it, I do it cheaper.
There's a very open question for AI/ML, which is, is there a way to actually build the company where you, no matter what can have good margins or software level margins.
So I feel like we're going to this escalation of margin crisis. You had traditional software, like in the Microsoft era, say where you ship software to 80% margins because you write it and you shipped it. And copying bits is basically free. You have 80% margins. Now we've have the cloud era, which I just walked through where you have a margin crisis where it is possible to run it on low margins.
But it's something that you have to tackle later on, which is why people think about re-architecting and repatriation.
Now we've got the AI/ML one, which is there's a fundamental question. And it's interesting to talk about is, is it even possible, no matter what you do, to do this on good margins? And the reason that question comes up is if you look at what it takes to create a model, and I'm going to shut up in a second, but if you look at what it takes to create one of these data companies, you have to create a model per customer.
BD - Yeah.
MC - And that's incredibly compute intensive to do it. And then to improve the accuracy of any single model, for example, you require just a ton more data. So you basically have a dis-economy of scale, which is in order to stay ahead, you've got to do more and it costs a lot more.
And so I feel like we're having a margin crisis on top of a margin crisis, like all the cloud margin costs and now the actual structural algorithm cost per AI/ML.
BD - So Martin there's one thing I wanted to drill into. There was this thing about repatriation, because I think that's a bit of a controversial topic. The idea that somehow you can run your private infrastructure more cost-effectively than public-cloud infrastructure.
So maybe you could just give us a little bit of insight on why that's true or back up that assertion.
MC - Yeah, so we've now seen a number of cases I think in the industry to really understand what's going on here. And it's an economic argument. It's strictly an economic argument and I kind of penciled it out, but I want to be a little bit clearer which is, if you look at dollars out the door on any given month, it never makes sense to build a data center, right? Because it takes a lot of dollars out the door in order to do that. However, if you look at multiples of revenue to the valuation of a company, all of a sudden it makes sense, right?
So if you've got 80% gross margins and you're growing at 2X, it may be 10X revenue, for the value of the company. And if your COGS, if your margins are say 40%, it could be 5X. Now that could be the difference between a $10 and a $20 billion company. Now, can you build a data center for $10 billion? The answer is yes, you can buy a whole bunch of them, right?
And then if you purpose built a data center for your app, can you make it more efficient than the cloud? Absolutely, because this is standard. The cloud is built for the long tail of small apps because that's what it caters to. This is nobody's fault, here, it's just the system.
So if you have a sufficiently large workload that you've been focusing on growth where the company slows down, let's take any online SaaS service and that's impacting your margins and therefore it's impacting the valuation of the company. It's actually quite easy to make the argument that, from a shareholder standpoint, it's far, far cheaper to build a data center than not.
BD - Wow, that's brilliant analysis.
We will give people a chance to go and find other ways to dig deeper into some of these topics, but a super interesting discussion Martin.
And I want to say thanks for your time.
MC - Thank you so much.
BD - Alright, cheers. And we'll see you soon.